Edge Computing
What is Edge Computing?
The word edge in this context means a geographic distribution. Edge computing is computing that’s done at or near the source of the data, instead of relying on the cloud at one of a dozen data centres to do all the work. It does not mean that the cloud will disappear. It means the cloud is coming to you. By placing computing services closer to these locations, users benefit from faster and more reliable services. Edge computing is one way that a company can use and distribute a common pool of resources across a large number of locations.Why do we need edge
computing?
The explosive growth and increasing computing
power of IoT devices has resulted in unprecedented volumes of data. And data
volumes will continue to grow as 5G networks increase the number of connected
mobile devices.
In the past, the promise of cloud and
AI was to automate and speed innovation by driving actionable insight from
data. But the unprecedented scale and complexity of data that’s created by
connected devices has outpaced network and infrastructure capabilities.
Sending all that device-generated data to a
centralized data centre or to the cloud causes bandwidth and latency issues.
Edge computing offers a more efficient alternative: data is processed and analysed
closer to the point where it's created. As data does not traverse over a
network to a cloud or data centre to be processed, latency is significantly
reduced. Edge computing — and mobile edge computing on 5G networks — enables
faster and more comprehensive data analysis, creating the opportunity for
deeper insights, faster response times and improved customer experiences.
What does the future hold for edge computing?
The potential of edge computing is extremely high, according
to research firm Gartner. The firm predicted two years ago that by 2025, a
whopping 75 percent of enterprise data would be generated and processed at
“the edge.” They say that in five years, the majority of enterprise data could
bypass the cloud entirely.
That being said, edge computing is still in its infancy and
not quite ready for primetime yet. Gartner’s report admitted as much, noting
that just 10 percent of enterprise data was generated and processed at the edge
in 2018.
Use Cases:
Some of the use cases are listed below:
1)
Autonomous
vehicles – With edge computing
vehicles will be able to communicate with each
other with ultra-low latency.
2)
Remote
monitoring of assets in the oil and gas industry - Edge
computing enables real-time analytics with processing much closer to the asset,
meaning there is less reliance on good quality connectivity to a centralised
cloud.
3) Smart grid - Sensors and IoT devices
connected to an edge platform in factories, plants and offices can be used to
monitor energy use and analyse their consumption in real-time.
4) Predictive maintenance - IoT sensors
will help monitor machine health with low latencies and perform analytics in
real-time thereby avoiding machine failure.
5) Healthcare - An edge on the hospital
site could process data locally to maintain data privacy. Edge also enables
right-time notifications to practitioners of unusual patient trends or
behaviours (through analytics/AI), and creation of 360-degree view patient
dashboards for full visibility.
6)
Virtualised
radio networks and 5G (vRAN) – Edge servers can help
the RAN hardware to do complex
processing with a low latency.
7)
Cloud
gaming - Cloud gaming companies are looking to build edge
servers as close to gamers as possible in order to reduce latency and provide a
fully responsive and immersive gaming experience.
8)
Content
delivery - Content providers are looking to distribute Content
Delivery Networks (CDNs) even more widely to the edge, thus guaranteeing
flexibility and customisation on the network depending on user traffic demands.
9) Smart homes - Sensitive information can be processed at the edge. As an example, the time taken for voice-based assistant devices such as Amazon’s Alexa to respond would be much faster.
10) Traffic management – Edge computing helps in optimising bus frequency given fluctuations in demand, managing the opening and closing of extra lanes, and, in future, managing autonomous car flows.
Challenges:
For “the edge” to become as popular as “the cloud” in the
tech industry, a large number of challenges will need to be
tackled: -
111) These include the
development of compact devices with outsized processing power.
2)2)The creation of software
that enables companies to remotely monitor and update a limitless number of
edge devices from across the world.
3)3) Better security
technology and protocols to keep everything safe.
Advantages
1)
Improved response times and latency across all devices.
2) Decreased data real estate creates
less risk in corporate security.
3) Reduced bandwidth reduces transmission
costs.
4) Economy of scale through edge devices.
Disadvantages
1)
Geographic Disparities: Fewer network devices and skilled implementers.
2)
Greater difficulty preventing and monitoring security breaches.
3)
Loss of data with potential energy.
4)
Cost and storage capacity needs.
Conclusion:
Edge computing
has both its advantages and disadvantages, but most IT experts agree that it
isn’t going away, especially with the forecasted growth of 5G access in the
near future. More users are using more kinds of devices at an incessant pace,
meaning that edge computing and the way it’s used are changing frequently
too.
With edge computing, things have become even more efficient. As a
result, the quality of business operations has become higher.
Edge computing is a viable solution for data-driven operations that
require lightning-fast results and a high level of flexibility, depending on
the current state of things.
Credits & References: Soham Bopardikar( Team Tech Tuesday)
1) https://en.wikipedia.org/wiki/Edge_computing
2) https://stlpartners.com/edge_computing/
3) https://www.ibm.com/in-en/cloud/what-is-edge-computing
4) https://builtin.com/cloud-computing/future-edge-computing
5) https://www.datamation.com/edge-computing
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